Vaginal carriage of Group B Streptococcus (GBS) is a maternal and child health issue. Our objective was to determine the prevalence of GBS carriage;identify the factors associated with this carriage and determine the ...Vaginal carriage of Group B Streptococcus (GBS) is a maternal and child health issue. Our objective was to determine the prevalence of GBS carriage;identify the factors associated with this carriage and determine the antibiotic sensitivity of the isolated strains. We conducted a cross-sectional and prospective study in rural Senegal (in the health district of Sokone). Socio-demographic, clinical and gynaeco-obstetrical data were collected. Vaginal swabs were taken by the midwives on specific settings in order to test for GBS and other High Risk Vaginal Bacteria (HRVB). Antibiotic susceptibility testing was done according to the recommendations of the CA SFM/EUCAST 2020. In total, 100 pregnant women were targeted and 97 pregnant women were included. Their age ranged from 18 to 40 years with 64.9% (63/97) of participants belonging to the “20 - 30” age group. The overall prevalence of Group B Streptococcus carriage was 15.5% (15/97). However, the proportion of women with at least one high risk infectious bacteria was 29.89% (29/97). No statistically significant differences were found between GBS carriage and the potential factors studied. However, the study also looked for the presence of other high-risk bacteria and coinfections were indeed found between GBS and E. coli and Staphylococcus aureus. Antibiotic susceptibility testing shows that GBS strains were fully susceptible to penicillin G, erythromycin, clindamycin, chloramphenicol, rifampicin and vancomycin. Sensitivities to norfloxacin and gentamycin were 73.3% and 86.7% respectively. In contrast, high resistance to tetracycline (86.7%) was observed. GBS carriage remains a major public health issue because of its consequences for the mother and the newborn. Correct screening and proper monitoring of strain susceptibility remain one of the most effective means of patient management and care.展开更多
This work addresses the problem of supervised classification for highly correlated highdimensional data describing non-independent observations to identify SNPs related to a phenotype.We use a general penalized linear...This work addresses the problem of supervised classification for highly correlated highdimensional data describing non-independent observations to identify SNPs related to a phenotype.We use a general penalized linear mixed model with a single random effect that performs simultaneous SNP selection and population structure adjustment in highdimensional prediction models.Specifically,the model simultaneously selects variables and estimates their effects,taking into account correlations between individuals.Single nucleotide polymorphisms(SNPs)are a type of genetic variation and each SNP represents a difference in a single DNA building block,namely a nucleotide.Previous research has shown that SNPs can be used to identify the correct source population of an individual and can act in isolation or simultaneously to impact a phenotype.In this regard,the study of the contribution of genetics in infectious disease phenotypes is of great importance.In this study,we used uncorrelated variables from the construction of blocks of correlated variables done in a previous work to describe the most related observations of the dataset.The model was trained with 90%of the observations and tested with the remaining 10%.The best model obtained with the generalized information criterion(GIC)identified the SNP named rs2493311 located on the first chromosome of the gene called PRDM16((PR/SET domain 16))as the most decisive factor in malaria attacks.展开更多
文摘Vaginal carriage of Group B Streptococcus (GBS) is a maternal and child health issue. Our objective was to determine the prevalence of GBS carriage;identify the factors associated with this carriage and determine the antibiotic sensitivity of the isolated strains. We conducted a cross-sectional and prospective study in rural Senegal (in the health district of Sokone). Socio-demographic, clinical and gynaeco-obstetrical data were collected. Vaginal swabs were taken by the midwives on specific settings in order to test for GBS and other High Risk Vaginal Bacteria (HRVB). Antibiotic susceptibility testing was done according to the recommendations of the CA SFM/EUCAST 2020. In total, 100 pregnant women were targeted and 97 pregnant women were included. Their age ranged from 18 to 40 years with 64.9% (63/97) of participants belonging to the “20 - 30” age group. The overall prevalence of Group B Streptococcus carriage was 15.5% (15/97). However, the proportion of women with at least one high risk infectious bacteria was 29.89% (29/97). No statistically significant differences were found between GBS carriage and the potential factors studied. However, the study also looked for the presence of other high-risk bacteria and coinfections were indeed found between GBS and E. coli and Staphylococcus aureus. Antibiotic susceptibility testing shows that GBS strains were fully susceptible to penicillin G, erythromycin, clindamycin, chloramphenicol, rifampicin and vancomycin. Sensitivities to norfloxacin and gentamycin were 73.3% and 86.7% respectively. In contrast, high resistance to tetracycline (86.7%) was observed. GBS carriage remains a major public health issue because of its consequences for the mother and the newborn. Correct screening and proper monitoring of strain susceptibility remain one of the most effective means of patient management and care.
文摘This work addresses the problem of supervised classification for highly correlated highdimensional data describing non-independent observations to identify SNPs related to a phenotype.We use a general penalized linear mixed model with a single random effect that performs simultaneous SNP selection and population structure adjustment in highdimensional prediction models.Specifically,the model simultaneously selects variables and estimates their effects,taking into account correlations between individuals.Single nucleotide polymorphisms(SNPs)are a type of genetic variation and each SNP represents a difference in a single DNA building block,namely a nucleotide.Previous research has shown that SNPs can be used to identify the correct source population of an individual and can act in isolation or simultaneously to impact a phenotype.In this regard,the study of the contribution of genetics in infectious disease phenotypes is of great importance.In this study,we used uncorrelated variables from the construction of blocks of correlated variables done in a previous work to describe the most related observations of the dataset.The model was trained with 90%of the observations and tested with the remaining 10%.The best model obtained with the generalized information criterion(GIC)identified the SNP named rs2493311 located on the first chromosome of the gene called PRDM16((PR/SET domain 16))as the most decisive factor in malaria attacks.
